Transceptor NRT1.1 and receptor-kinase QSK1 complex controls PM H+-ATPase activity under low nitrate.

NRT1.1, a nitrate transceptor, plays an important role in nitrate binding, sensing, and nitrate-dependent lateral root (LR) morphology. However, little is known about NRT1.1-mediated nitrate signaling transduction through plasma membrane (PM)-localized proteins. Through in-depth phosphoproteome profiling using membranes of Arabidopsis roots, we identified receptor kinase QSK1 and plasma membrane H+-ATPase AHA2 as potential downstream components of NRT1.1 signaling in a mild low-nitrate (LN)-dependent manner. QSK1, as a functional kinase and molecular link, physically interacts with NRT1.1 and AHA2 at LN and specifically phosphorylates AHA2 at S899. Importantly, we found that LN, not high nitrate (HN), induces formation of the NRT1.1-QSK1-AHA2 complex in order to repress the proton efflux into the apoplast by increased phosphorylation of AHA2 at S899. Loss of either NRT1.1 or QSK1 thus results in a higher T947/S899 phosphorylation ratio on AHA2, leading to enhanced pump activity and longer LRs under LN. Our results uncover a regulatory mechanism in which NRT1.1, under LN conditions, promotes coreceptor QSK1 phosphorylation and enhances the NRT1.1-QSK1 complex formation to transduce LN sensing to the PM H+-ATPase AHA2, controlling the phosphorylation ratio of activating and inhibitory phosphorylation sites on AHA2. This then results in altered proton pump activity, apoplast acidification, and regulation of NRT1.1-mediated LR growth.

Multiomics Analysis Reveals the Chemical and Genetic Bases of Pigmented Potato Tuber.

Anthocyanins and carotenoids determine the diversity of potato tuber flesh pigmentation; here, the underlying chemical and genetic bases were elucidated by multiomics analyses. A total of 31 anthocyanins and 30 carotenoids were quantified in five differently pigmented tubers. Cyanidin and pelargonidin derivatives determined the redness, while malvidin, petunidin, and delphinidin derivatives contributed to purpleness. Violaxanthin derivatives determined the light-yellow color, while zeaxanthin and antheraxanthin derivatives further enhanced the deep-yellow deposition. Integrated transcriptome and proteome analyses identified that F3'5'H highly enhanced anthocyanin biosynthesis in purple flesh and was responsible for metabolic divergence between red and purple samples. BCH2 significantly enhanced carotenoid biosynthesis in yellow samples and along with ZEP, NCED1, and CCD1 genes determined metabolic divergence between light and deep-yellow samples. The weighted correlation network analysis constructed a regulatory network revealing the central role of AN1 in regulating anthocyanin biosynthesis, and 10 new transcription factors related to anthocyanin and carotenoid metabolism regulation were identified. Our findings provide targeted genes controlling tuber pigmentation, which will be meaningful for the genetic manipulation of tuber quality improvement.

ScRNA-seq and ST-seq in liver research.

Spatial transcriptomics, which combine gene expression data with spatial information, has quickly expanded in recent years. With application of this method in liver research, our knowledge about liver development, regeneration, and diseases have been greatly improved. While this field is moving forward, a variety of problems still need to be addressed, including sensitivity, limited capacity to obtain exact single-cell information, data processing methods, as well as others. Methods like single-cell RNA sequencing (scRNA-seq) are usually used together with spatial transcriptome sequencing (ST-seq) to clarify cell-specific gene expression. In this review, we explore how advances of scRNA-seq and ST-seq, especially ST-seq, will pave the way to new opportunities to investigate fundamental questions in liver research. Finally, we will discuss the strengths, limitations, and future perspectives of ST-seq in liver research.

Phosphoproteomics Profiling of Receptor Kinase Mutants.

The transmembrane receptor kinase family is the largest protein kinase family in Arabidopsis. Many members of this family play critical roles in plant signaling pathways. However, many of these kinases have yet uncharacterized functions and very little is known about the direct substrates of these kinases. We have developed the "ShortPhos" method, an efficient and simple mass spectrometry (MS)-based phosphoproteomics protocol to perform comparative phosphopeptide profiling of knockout mutants of receptor-like kinases. Through this method, we are able to better understand the functional roles of plant kinases in the context of their signaling networks.

Phosphoproteomics Analysis of Plant Root Tissue.

Plants absorb water and nutrients from soil through roots and transmit these resources through the xylem to the shoot. Roots therefore participate in information and material transduction as well as signal communication with the shoot. The importance of reversible protein phosphorylation in the regulation of plant growth and development has been amply demonstrated through decades of research. Here, we present a simple mass spectrometry-based shotgun phosphoproteomics protocol for Arabidopsis root tissue. Through this method, we can profile the Arabidopsis root phosphoproteome and construct signal networks of key proteins to better understand their roles in plant growth and development.

Plant Phosphopeptide Identification and Label-Free Quantification by MaxQuant and Proteome Discoverer Software.

Both the phosphorylation and dephosphorylation of plant proteins is involved in multiple biological processes, especially in regard to signal transduction. The identification of phosphopeptides from MS (mass spectrometry)-based methods and their subsequent quantification play an important role in plant phosphoproteomics analysis. Phosphopeptide(s) identification and label-free quantification can determine dynamic changes of phosphorylation events in plants. Both MaxQuant and Proteome Discoverer are professional software tools used to identify and quantify large-scale MS-based phosphoproteomic data. This chapter gives a detailed workflow of MaxQuant and Proteome Discoverer software to analyze large amounts of phosphoproteomic-related MS data for the identification and quantification of label-free plant phosphopeptides.

On the role of the mitochondrial 2-oxoglutarate dehydrogenase complex in amino acid metabolism.

Mitochondria are tightly linked to cellular nutrient sensing, and provide not only energy, but also intermediates for the de novo synthesis of cellular compounds including amino acids. Mitochondrial metabolic enzymes as generators and/or targets of signals are therefore important players in the distribution of intermediates between catabolic and anabolic pathways. The highly regulated 2-oxoglutarate dehydrogenase complex (OGDHC) participates in glucose oxidation via the tricarboxylic acid cycle. It occupies an amphibolic branch point in the cycle, where the energy-producing reaction of the 2-oxoglutarate degradation competes with glutamate (Glu) synthesis via nitrogen incorporation into 2-oxoglutarate. To characterize the specific impact of the OGDHC inhibition on amino acid metabolism in both plant and animal mitochondria, a synthetic analog of 2-oxoglutarate, namely succinyl phosphonate (SP), was applied to living systems from different kingdoms, both in situ and in vivo. Using a high-throughput mass spectrometry-based approach, we showed that organisms possessing OGDHC respond to SP by significantly changing their amino acid pools. By contrast, cyanobacteria which lack OGDHC do not show perturbations in amino acids following SP treatment. Increases in Glu, 4-aminobutyrate and alanine represent the most universal change accompanying the 2-oxoglutarate accumulation upon OGDHC inhibition. Other amino acids were affected in a species-specific manner, suggesting specific metabolic rearrangements and substrate availability mediating secondary changes. Strong perturbation in the relative abundance of amino acids due to the OGDHC inhibition was accompanied by decreased protein content. Our results provide specific evidence of a considerable role of OGDHC in amino acid metabolism.

A topological map of the compartmentalized Arabidopsis thaliana leaf metabolome.

BACKGROUND: The extensive subcellular compartmentalization of metabolites and metabolism in eukaryotic cells is widely acknowledged and represents a key factor of metabolic activity and functionality. In striking contrast, the knowledge of actual compartmental distribution of metabolites from experimental studies is surprisingly low. However, a precise knowledge of, possibly all, metabolites and their subcellular distributions remains a key prerequisite for the understanding of any cellular function. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe results for the subcellular distribution of 1,117 polar and 2,804 lipophilic mass spectrometric features associated to known and unknown compounds from leaves of the model plant Arabidopsis thaliana. Using an optimized non-aqueous fractionation protocol in conjunction with GC/MS- and LC/MS-based metabolite profiling, 81.5% of the metabolic data could be associated to one of three subcellular compartments: the cytosol (including the mitochondria), vacuole, or plastids. Statistical analysis using a marker-'free' approach revealed that 18.5% of these metabolites show intermediate distributions, which can either be explained by transport processes or by additional subcellular compartments. CONCLUSION/SIGNIFICANCE: Next to a functional and conceptual workflow for the efficient, highly resolved metabolite analysis of the fractionated Arabidopsis thaliana leaf metabolome, a detailed survey of the subcellular distribution of several compounds, in the graphical format of a topological map, is provided. This complex data set therefore does not only contain a rich repository of metabolic information, but due to thorough validation and testing by statistical methods, represents an initial step in the analysis of metabolite dynamics and fluxes within and between subcellular compartments.

Sample amount alternatives for data adjustment in comparative cyanobacterial metabolomics.

Here we describe an integrative protocol for metabolite extraction and the measurement of three cellular constituents, chlorophyll a, total protein, and glycogen from the same small volume of cyanobacterial cultures that can be used as alternative sample amount parameters for data adjustment in comparative metabolome studies. We conducted recovery experiments to assess the robustness and reproducibility of the measurements obtained for the cellular constituents. Also, we have chosen three profile-intrinsic parameters derived from gas chromatography-mass spectrometry (GC/MS) data in order to test their utility for spectral data adjustment. To demonstrate the relevance of these six parameters, we analyzed three cyanobacteria with greatly different morphologies, comprising a unicellular, a filamentous, and a filamentous biofilm-forming strain. Comparative analysis of GC/MS data from cultures grown under standardized conditions indicated that adjustment of the corresponding metabolite profiles by any of the measured cellular constituents or chosen intrinsic parameters led to similar results with respect to sample cohesion and strain separation. Twenty-one metabolites significantly enriched for the carbohydrate and amine superclasses are mainly responsible for strain separation, with a majority of the remaining metabolites contributing to sample group cohesion. Therefore, we conclude that any of the parameters tested in this study can be used for spectral data adjustment of cyanobacterial strains grown under controlled conditions. However, their use for the differentiation between different stresses or physiological states within a strain remains to be shown. Interestingly, both the adjustment approaches and statistical tests applied effected the detection of metabolic differences and their patterns among the analyzed strains.

Analysis of the compartmentalized metabolome - a validation of the non-aqueous fractionation technique.

With the development of high-throughput metabolic technologies, a plethora of primary and secondary compounds have been detected in the plant cell. However, there are still major gaps in our understanding of the plant metabolome. This is especially true with regards to the compartmental localization of these identified metabolites. Non-aqueous fractionation (NAF) is a powerful technique for the determination of subcellular metabolite distributions in eukaryotic cells, and it has become the method of choice to analyze the distribution of a large number of metabolites concurrently. However, the NAF technique produces a continuous gradient of metabolite distributions, not discrete assignments. Resolution of these distributions requires computational analyses based on marker molecules to resolve compartmental localizations. In this article we focus on expanding the computational analysis of data derived from NAF. Along with an experimental workflow, we describe the critical steps in NAF experiments and how computational approaches can aid in assessing the quality and robustness of the derived data. For this, we have developed and provide a new version (v1.2) of the BestFit command line tool for calculation and evaluation of subcellular metabolite distributions. Furthermore, using both simulated and experimental data we show the influence on estimated subcellular distributions by modulating important parameters, such as the number of fractions taken or which marker molecule is selected. Finally, we discuss caveats and benefits of NAF analysis in the context of the compartmentalized metabolome.

Assessment of sampling strategies for gas chromatography-mass spectrometry (GC-MS) based metabolomics of cyanobacteria.

Metabolomics is the comprehensive analysis of the small molecules that compose an organism's metabolism. The main limiting step in microbial metabolomics is the requirement for fast and efficient separation of microbes from the culture medium under conditions in which metabolism is rapidly halted. In this article we compare three different sampling strategies, quenching, filtering, and centrifugation, for arresting the metabolic activities of two morphologically diverse cyanobacteria, the unicellular Synechocystis sp. PCC 6803 and the filamentous Nostoc sp. PCC 7120 for GC-MS analysis. We demonstrate that each sampling technique produces internally consistent and reproducible data, however, cold methanol-water quenching caused leakage and substantial loss of metabolites from various compound classes, while fast filtering and centrifugation produced quite similar metabolite pool sizes, even for metabolites with predicted high turnover. This indicates that cyanobacterial metabolic pools, as measured by GC-MS, do not show high turnover under standard growing conditions. As well, using stable (13)C labeling we show the biological origin of some of the consistently observed unknown analytes. With the development of these techniques, we establish the basis for broad scale comparative metabolite profiling of cyanobacteria.

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

BACKGROUND: Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. RESULTS: Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. CONCLUSION: PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.

The effect of cellulose overproduction on binding and biofilm formation on roots by Agrobacterium tumefaciens.

Agrobacterium tumefaciens growing in liquid attaches to the surface of tomato and Arabidopsis thaliana roots, forming a biofilm. The bacteria also colonize roots grown in sterile quartz sand. Attachment, root colonization, and biofilm formation all were markedly reduced in celA and chvB mutants, deficient in production of cellulose and cyclic beta-(1,2)-D-glucans, respectively. We have identified two genes (celG and cell) in which mutations result in the overproduction of cellulose as judged by chemical fractionation and methylation analysis. Wild-type and chvB mutant strains carrying a cDNA clone of a cellulose synthase gene from the marine urochordate Ciona savignyi also overproduced cellulose. The overproduction in a wild-type strain resulted in increased biofilm formation on roots, as evaluated by light microscopy, and levels of root colonization intermediate between those of cellulose-minus mutants and the wild type. Overproduction of cellulose by a nonattaching chvB mutant restored biofilm formation and bacterial attachment in microscopic and viable cell count assays and partially restored root colonization. Although attachment to plant surfaces was restored, overproduction of cellulose did not restore virulence in the chvB mutant strain, suggesting that simple bacterial binding to plant surfaces is not sufficient for pathogenesis.

Cross-species microarray transcript profiling reveals high constitutive expression of metal homeostasis genes in shoots of the zinc hyperaccumulator Arabidopsis halleri.

Arabidopsis halleri ssp. halleri (accession Langelsheim) is a naturally selected zinc (Zn)- and cadmium-tolerant Zn hyperaccumulator. This plant differs strikingly from its close relative A. thaliana by accumulating Zn specifically in above-ground tissues. A. thaliana GeneChips were used in order to identify, on a transcriptome-wide scale, genes with a potential involvement in cellular metal uptake or detoxification in the shoots of A. halleri. Compared to A. thaliana, transcript abundance of several genes was found and confirmed to be substantially higher in A. halleri after 4 days of exposure to low as well as high Zn concentrations in the hydroponic culture medium. The identified candidate genes encode proteins closely related to the following A. thaliana proteins: AtZIP6, a putative cellular Zn uptake system and member of the zinc-regulated transporter (ZRT)-iron regulated transporter (IRT)-like protein (ZIP)-family of metal transporters, the putative P-type metal ATPase AtHMA3, the cation diffusion facilitator ZAT/AtCDF1, and the nicotianamine synthase AtNAS3. Heterologous expression in mutant strains of the yeast Saccharomyces cerevisiae suggested that AhHMA3, AhCDF1-3, and AhNAS3 can function in cellular Zn detoxification. Our data indicate that, at the transcript level, the Zn tolerance strategy of A. halleri involves high constitutive expression of metal homeostasis genes in the shoots to accommodate higher basal levels of Zn accumulation, and possibly to prepare for sudden increases in Zn influx into shoot cells. Furthermore, profiling of metal homeostasis gene transcripts in shoot and root tissues by real-time RT-PCR indicated that A. halleri and A. thaliana respond differently to changes in plant Zn status.